
Non-destructive compression gateway that drops between coding agents and LLMs to cut input tokens by up to 85% without changing the agent.
Non-destructive compression gateway that drops between coding agents and LLMs to cut input tokens by up to 85% without changing the agent.
Paritok is an Apache-2.0 gateway that sits between any coding agent (Claude Code, Cursor, Codex, OpenHands, or any OpenAI-compatible client) and the upstream LLM, non-destructively compressing tool schemas, file reads, and stale history on the fly. Three levers stack: MCP-heavy tool blocks are stubbed and kept cache-stable, file reads and tool outputs are compressed by a 4B code-native model (trained on 45K real agent trajectories) that preserves identifiers and error strings, and older turns beyond a configurable window are summarized once. Everything is tagged, so when the agent needs the exact bytes it calls read_original(ref) and gets them locally — no extra LLM round-trip. Deployment is one environment variable (ANTHROPIC_BASE_URL=http://127.0.0.1:8080). Self-hosting is free forever and runs the 4B model at ~2.5GB Q4 on any 8GB GPU (tool filter runs on CPU); the hosted GPU tier is free through August and priced per 1M input tokens after.
Paritok is a non-destructive compression gateway that seamlessly integrates between coding agents and large language models (LLMs). It can reduce input tokens by up to 85% without altering the functionality of the agents, enhancing efficiency and performance in AI applications.
Paritok serves as a powerful intermediary between coding agents and large language models (LLMs), primarily aimed at optimizing data processing. By employing advanced compression techniques, it effectively reduces the number of tokens required for input, leading to significant savings in computational resources.
For instance, in a scenario where a coding agent needs to process extensive datasets, Paritok can compress inputs, allowing the agent to focus on essential data without losing context. This is especially beneficial in environments where rapid processing and cost efficiency are paramount, such as cloud-based AI applications.
Paritok operates by streamlining the interaction between AI agents and tools through advanced compression techniques, reducing input tokens significantly while maintaining efficiency. It enhances performance through features like tool schema compression, local data recall, and privacy-focused self-hosting, making it ideal for intensive coding workflows.
Paritok is designed to optimize the performance of AI agents, particularly in complex coding environments. Here’s how its core features function:
Drop-In Gateway: With just one environment variable (ANTHROPIC_BASE_URL), Paritok reroutes your agent seamlessly through its platform. This setup requires no modifications to the agent, prompts, or tools, making it easy to implement.
Tool Schema Compression: Paritok employs a sophisticated mechanism to compress approximately 46 schema tool blocks (about 29,000 tokens) down to around 8,000 tokens per interaction. This selective retention of relevant tools while stubbing the others ensures that users can maintain context without overwhelming their system’s capacity.
Code-Native 4B Model: Utilizing a 4 billion parameter compression model trained on 45,000 real agent trajectories, Paritok effectively reduces file read times and outputs to roughly 26% of their original size. This model retains essential identifiers, paths, and errors, thereby enabling more efficient coding sessions.
read_original Recall: Every compressed segment is tagged, allowing the agent to retrieve exact bytes locally with the command read_original(ref). This feature eliminates the need for an additional interaction to fetch data, saving time and resources.
Stale History Summarization: To manage context effectively, turns that exceed a configurable recent window are summarized once, ensuring that recent interactions remain intact and preventing overflow.
For teams managing MCP-heavy workflows, Paritok significantly reduces input costs—estimations suggest a 54% reduction in token usage for a typical five-developer team could save around $6,550 annually.
Paritok offers several key features, including a Drop-In Gateway for seamless integration, Tool Schema Compression that significantly reduces token usage, and a Code-Native 4B Model designed for efficiency. These functionalities enhance performance and streamline the agent's operation without requiring extensive modifications.
Paritok is designed to enhance AI agent performance through innovative features:
Drop-In Gateway: This feature allows developers to integrate their agents seamlessly by using a single environment variable, ANTHROPIC_BASE_URL. This means that no changes are needed in the agent, prompts, or tools, making it an ideal solution for quick implementation.
Tool Schema Compression: Paritok effectively compresses 46-schema tool blocks, reducing the size from approximately 29,000 tokens to around 8,000 tokens per turn. By retaining only relevant tools and stubbing others, it maintains cache stability for each conversation, ensuring efficient use of resources and faster response times.
Code-Native 4B Model: The 4B compression model is specifically trained on 45,000 real agent trajectories. It adeptly preserves identifiers, paths, and error information while minimizing file reads and outputs to about 26% of their original size. This efficiency not only boosts performance but also reduces latency in response generation.
read_original Recall: This feature enhances data retrieval efficiency by tagging every compressed segment. When an agent requests read_original(ref), it retrieves exact bytes locally without consuming an additional turn, streamlining the interaction process.
Stale History Summarization: Paritok intelligently summarizes conversation turns that exceed a configurable recent window. This occurs when your context budget is filled, allowing recent turns to remain intact while managing overflow efficiently, thereby maintaining context relevance.
Paritok is designed for developers and teams engaged in MCP-heavy workflows, long coding sessions, and those seeking cost-effective solutions for coding agent management. It is particularly beneficial for enterprises looking to optimize performance while ensuring data privacy and lowering operational costs.
Paritok serves a diverse audience, especially those in software development and engineering who handle complex workflows. Here’s how it meets various needs:
MCP-Heavy Workflows: Paritok excels in environments where shipping multiple MCP tool schemas is crucial. It allows agents to efficiently manage 70+ schemas per session, enhancing productivity and reducing workload bottlenecks.
Long Coding Sessions: For developers engaged in extended coding tasks, Paritok enables sessions that last three times longer. This is vital for projects requiring deep focus and creativity, preventing context saturation that often leads to reduced coding efficiency.
Cost Management: Paritok facilitates significant cost reduction, estimating savings of around 54% on input tokens for teams of five developers engaged in approximately 20-turn sessions with Claude Sonnet. This translates to potential annual savings of about $6,550, making it an attractive option for budget-conscious teams.
Self-Hosted Privacy: With Paritok, businesses can route agent traffic through their own hardware, ensuring that sensitive data never leaves their network. A simple 8GB GPU setup is sufficient to handle the processing, making it accessible for many organizations.
Enterprise Cost Governance: Paritok includes features for compressing data at the gateway layer. This allows all coding agents within a team to benefit from reduced costs without necessitating engineering adjustments for each individual agent.
Paritok offers a free tier, allowing users to access basic features without any cost. For those seeking advanced functionalities, paid plans are available, typically starting at competitive prices that cater to various user needs and budgets.
Paritok has positioned itself as a versatile tool for users looking to enhance their productivity through AI-driven solutions. The free tier allows new users to explore its capabilities, including essential features that can assist with various tasks. This tier is perfect for individuals or small teams wanting to test the service without financial commitment.
For users who require more advanced features—such as enhanced analytics, integrations with third-party applications, or priority customer support—Paritok offers several paid plans. Pricing for these plans typically starts around $10 to $50 per month, depending on the level of service and number of users. The higher-tier plans often include additional tools designed for larger teams or enterprises, providing robust solutions for complex projects.
Users can upgrade to a paid plan easily through their account settings, allowing for seamless transition from the free tier while maintaining access to existing data and projects.
To get started with Paritok, visit https://www.paritok.com/ to sign up for an account. Once registered, you can explore the platform's features, tools, and resources tailored for efficient team collaboration and project management.
To begin using Paritok, follow these steps:
Sign Up: Navigate to Paritok's website and click on the "Sign Up" button. You will be prompted to enter your email address and create a password. Alternatively, you can sign up using your Google or Microsoft account for quicker access.
Explore Features: After signing in, take advantage of the user-friendly dashboard. Familiarize yourself with key features such as project timelines, task assignments, and collaborative tools. Paritok offers a variety of templates for different project types, making it easier to kick-start your planning.
Set Up Your Workspace: Create a new workspace for your team or project. You can invite team members by entering their email addresses. This feature enhances collaboration and ensures everyone is on the same page.
Utilize Resources: Access tutorials and help guides provided by Paritok to maximize your usage. Whether you need tips on project setup or best practices, these resources are invaluable for new users.
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